motion planning for multiple autonomous vehicles
DESCRIPTION
Motion Planning for Multiple Autonomous Vehicles . Introduction. Rahul Kala. Autonomous Vehicles. Software Architecture. Environment understanding. Sensor. Environment. Localization. Sensor fusion. Planning. Motion. Control. Map. Mission. Thesis. Static Obstacles. B. A. C. a. - PowerPoint PPT PresentationTRANSCRIPT
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School of Systems, Engineering, University of Reading
rkala.99k.orgApril, 2013
Motion Planning for Multiple Autonomous Vehicles
Rahul Kala
Introduction
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Autonomous Vehicles
Safety
Efficient Driving
Jam Avoidance
Coordination
Comfort
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Software Architecture
SensorEnvironment understanding
Sensor fusionLocalizationPlanning
Control Motion
Map Mission
Environment
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Motion Planning for Multiple Autonomous Vehicles
Thesis
Thesis
Trajectory Generation
Intelligent Management of
the Transportation
System
rkala.99k.org
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Motion Planning for Multiple Autonomous Vehicles
Trajectory Generation
rkala.99k.org
A
Static Obstacles
B
C
Select the best plan: (a) A overtakes B from right, B drifts left, A crosses the obstacles, C waits, (b) A follows B and both cross the obstacles while C waits, (c) B crosses the obstacles followed by C and A, (d) C crosses the obstacle a from its left, while A follows B to cross the others
a
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Motion Planning for Multiple Autonomous Vehicles
Key Contributions• Various aspects of unorganized traffic (operating without
lanes) are studied. • The problem of trajectory planning for unorganized traffic
in a diverse multi-vehicle scenario is studied, while the literature is largely focussed on the study of the organized counterpart.
• The algorithm framework is generalized to the cases in which traffic intermingles on both sides of a dual carriageway (or the vehicles partly occupy the wrong side) for higher traffic efficiency (usually implying overtaking).
• A new coordinate axis system called the road coordinate axis system is designed for enhanced performance with curved and variable width roads.
rkala.99k.org
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Organized and Unorganized Traffic
Organized
Image Courtesy: railway-technical.com, blogs.abc.net.au/
Unorganized
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Unorganized Traffic
Advantages• Larger Traffic
Bandwidth
• More overtakes/ more efficient
Disadvantages• Safety• Non-Clearer
Intentions• Large Lateral
Movements• Larger travel
distances• Less driving
comfort
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Unorganized Traffic
When better?
• Diverse widths• Diverse speeds• Speed diversity
necessitates overtakes
• E.g. Indian traffic!
Migration from Organized to Unorganized?
• Intelligent Vehicles will bring diversity
• Is future diverse?
• Current Defiance of lanes:
• Motorists driving in between lanes
• Overtakes by emergency vehicles
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Layers of PlanningStrategic – Where to go
and in which order
Sub-strategic - Route Planning
Middle tier – Validation, re-planning, plan extension
Trajectory generation
Control
Abst
ract
ion Merging Intersectio
ns
Parking Blockage
Normal roads
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Motion Planning for Multiple Autonomous Vehicles
Continual Planning
rkala.99k.org
Vision
Vehicle current position
Immediate Move
Trajectory
generation
Trajectory
validation
Trajectory
extension
Planning as the vehicle moves
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Per-Segment Planning
Segment 1
Segment 2
Segment 3Vehicle current position
Planned trajectory for
segment 1
Vehicle planned position
Obstacle
Moving by planned trajectory in segment 1 with a segment 1 only vision would result in vehicle coming too close to the obstacle. Hence segments are overlapped and the vehicle is re-planned at the entry of segment 2.
Overlapping segment breakup
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Communication – if available
Communication
Communication
Obstacle Discovery
LocalizationCollision Avoidance
Travel Plan
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Road Coordinate Axis System
waxPyxPyxP ,')''(),(
• Curved roads• Irregular width roads
Better suited for
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Motion Planning for Multiple Autonomous Vehicles
Intelligent Management of the Transportation System
rkala.99k.org
Road map of Reading, United Kingdom
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Motion Planning for Multiple Autonomous Vehicles
Key Contributions• The study is based upon the notion of
diversities, which may be speed based diversity or task based diversity.
• Both recurrent and non-recurrent traffic is studied to overcome congestion avoidance which means applicability to any region depending upon its dynamics.
• The different models studied vary from being mostly semi-autonomous to mostly non semi-autonomous, which covers all the stages of the evolution of traffic.
• Different traffic elements including traffic lights, lane changes and routing are incorporated in the study.
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Motion Planning for Multiple Autonomous Vehicles
Intelligent Management of the Transportation System
• Experiment new traffic behaviours • Traffic light, Dynamic Speed Lanes• Lane Booking, Road Booking• Density Regularization, Blockages, Re-routing
Dynamic Traffic Management
• Non-recurrent traffic• City based scenario• Short frequent re-planning• Single lane overtakes• Density and Traffic Light avoidance
Congestion Avoidance
• Recurrent Traffic• Route and Start Time Determination• Maximize probability of reaching on time and
minimize wait time• Cooperative traffic lights and lane changes
Reaching Destination
before Deadline
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Motion Planning for Multiple Autonomous Vehicles rkala.99k.org
Thank You
• Acknowledgements:• Commonwealth Scholarship Commission in the United Kingdom • British Council